Data Engineer

Software Finder•201 District, VA

19d•Onsite

About The Position

Software Finder is seeking skilled and motivated Data Engineers to join our growing Data Engineering team. This is a generalist AWS-focused role where you will own data pipelines end-to-end—from ingestion and transformation to delivering reliable data that supports business intelligence and strategic decision-making. The pipelines and data products you build will directly support revenue-driving systems and analytics, extending beyond internal reporting. This role also offers opportunities to expand into broader software engineering responsibilities as your expertise and the team’s needs evolve.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Data Science, Information Technology, or a related discipline.
2–3 years of professional experience in data engineering or a backend/software engineering role involving significant data work.
Strong SQL skills, including experience writing and optimizing complex queries.
Proficiency in Python for building data pipelines and automation workflows.
Hands-on experience with AWS data services such as S3, Glue, Redshift, Lambda, Athena, and EventBridge.
Practical experience with Apache Airflow or AWS Step Functions for workflow orchestration.
Strong understanding of data-modelling fundamentals, including normalization and dimensional modelling.
Familiarity with Git and collaborative software-development workflows.
Ability to troubleshoot data-quality issues, pipeline failures, and performance bottlenecks.
Strong analytical, problem-solving, and cross-functional communication skills.
Willingness to work onsite in Lahore from 11:00 AM to 8:00 PM PKT.

Nice To Haves

Experience with dbt for SQL-based data transformation.
Familiarity with Terraform or other infrastructure-as-code tools.
Experience with CI/CD pipelines using GitHub Actions, AWS CodePipeline, or similar tools.
Experience with data monitoring, observability, and pipeline-cost optimization.
Familiarity with AI coding assistants such as Claude Code.
Understanding of data governance, validation, and quality-control practices.
Interest in growing into broader backend or software engineering responsibilities.

Responsibilities

Design, build, deploy, and maintain scalable ETL/ELT pipelines on AWS.
Ingest and transform data from multiple source systems into the organization’s data warehouse.
Write, optimize, and maintain complex SQL queries for data transformation, modelling, and analytics.
Develop reliable data models that support BI dashboards, reporting, and business analysis.
Orchestrate workflows using Apache Airflow or AWS Step Functions.
Monitor pipeline health, investigate failures, and implement long-term solutions to recurring issues.
Collaborate closely with the BI team to improve data accuracy, consistency, and trustworthiness.
Establish feedback loops between Data Engineering and BI to address data-quality gaps.
Improve pipeline reliability, performance, observability, and cost efficiency.
Use AI-assisted development tools, such as Claude Code, to accelerate development and iteration.
Participate in code reviews and follow established engineering standards.
Maintain technical documentation for pipelines, data models, and workflows.
Gradually contribute to broader backend and software engineering initiatives.
Perform additional data engineering and technology-related tasks as assigned.